Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.Financial support for this study was provided by a grant from ZonMw (Grant number: 848015007). ZonMw had no role in designing the study, interpreting the data, writing the manuscript, and publishing the report

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim: To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods: A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results: Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion: This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies

Model-based effectiveness and cost-effectiveness of risk-based selection strategies for adjuvant chemotherapy in Dutch stage II colon cancer patients

Background: We aimed to evaluate the cost-effectiveness of risk-based strategies to improve the selection of surgically treated stage II colon cancer (CC) patients for adjuvant chemotherapy. Methods: Using the ‘Personalized Adjuvant TreaTment in EaRly stage coloN cancer’ (PATTERN) model, we evaluated five selection strategies: (1) no chemotherapy, (2) Dutch guideline recommendations assuming observed adherence, (3) Dutch guideline recommendations assuming perfect adherence, (4) biomarker mutation OR pT4 stage strategy in which patients with MSS status combined with a pT4 stage or a mutation in BRAF and/or KRAS receive chemotherapy assuming perfect adherence and (5) biomarker mutation AND pT4 stage strategy in which patients with MSS status combined with a pT4 stage tumor and a BRAF and/or KRAS mutation receive chemotherapy assuming perfect adherence. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Analyses were conducted from a societal perspective. The robustness of model predictions was assessed in sensitivity analyses. Results: The reference strategy, that is, no adjuvant chemotherapy, resulted in 139 CC deaths in a cohort of 1000 patients, 8.077 QALYs pp and total costs of €22,032 pp. Strategies 2–5 were more effective (range 8.094–8.217 QALYs pp and range 118–136 CC deaths per 1000 patients) and more costly (range €22,404–€25,102 pp). Given a threshold of €50,000/QALY, the optimal use of resources would be to treat patients with either the full adherence strategy and biomarker mutation OR pT4 stage strategy. Conclusion: Selection of stage II CC patients for chemotherapy can be improved by either including biomarker status in the selection strategy or by improving adherence to the Dutch guideline recommendations

Model-based evaluation of the cost effectiveness of 3 versus 6 months’ adjuvant chemotherapy in high-risk stage II colon cancer patients

Background: Our aim was to evaluate the cost effectiveness of 3 months’ adjuvant chemotherapy versus 6 months in high-risk (T4 stage + microsatellite stable) stage II colon cancer (CC) patients. Methods: Using the validated PATTERN Markov cohort model, which simulates the disease progression of stage II CC patients from diagnosis to death, we first evaluated a reference strategy in which high-risk patients were treated with chemotherapy for 6 months. In the second strategy, treatment duration was shortened to 3 months. Both strategies were evaluated for CAPOX (capecitabine plus oxaliplatin) and FOLFOX (fluorouracil, leucovorin and oxaliplatin). Based on trial data, we assumed that shortened treatment duration compared with a 6-month regimen was equally effective for CAPOX and less effective for FOLFOX. Adverse events were highest in the 6-month strategy. Analyses were conducted from a societal perspective using a lifelong time horizon. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Incremental net monetary benefit (iNMB) was calculated using a willingness-to-pay value of €50,000/QALY. Results: For CAPOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €41,257 pp. The 3-month strategy resulted in an equal number of CC deaths, but higher QALYs (6.80 pp) and lower costs (€37,645 pp), leading to a iNMB of €8454 per person for 3 months versus 6 months. For FOLFOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €47,135 pp. The 3-month strategy resulted in more CC deaths (393), lower QALYs (6.19 pp) and lower costs (€44,389 pp). An iNMB of −€23,189 was found for 3 months versus 6 months. Conclusion: Our findings indicate that 3 months’ adjuvant chemotherapy should be considered as standard of care in high-risk stage II CC patients for CAPOX, but not for FOLFOX

Model-based effectiveness and cost-effectiveness of risk-based selection strategies for adjuvant chemotherapy in Dutch stage II colon cancer patients

Background: We aimed to evaluate the cost-effectiveness of risk-based strategies to improve the selection of surgically treated stage II colon cancer (CC) patients for adjuvant chemotherapy. Methods: Using the ‘Personalized Adjuvant TreaTment in EaRly stage coloN cancer’ (PATTERN) model, we evaluated five selection strategies: (1) no chemotherapy, (2) Dutch guideline recommendations assuming observed adherence, (3) Dutch guideline recommendations assuming perfect adherence, (4) biomarker mutation OR pT4 stage strategy in which patients with MSS status combined with a pT4 stage or a mutation in BRAF and/or KRAS receive chemotherapy assuming perfect adherence and (5) biomarker mutation AND pT4 stage strategy in which patients with MSS status combined with a pT4 stage tumor and a BRAF and/or KRAS mutation receive chemotherapy assuming perfect adherence. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Analyses were conducted from a societal perspective. The robustness of model predictions was assessed in sensitivity analyses. Results: The reference strategy, that is, no adjuvant chemotherapy, resulted in 139 CC deaths in a cohort of 1000 patients, 8.077 QALYs pp and total costs of €22,032 pp. Strategies 2–5 were more effective (range 8.094–8.217 QALYs pp and range 118–136 CC deaths per 1000 patients) and more costly (range €22,404–€25,102 pp). Given a threshold of €50,000/QALY, the optimal use of resources would be to treat patients with either the full adherence strategy and biomarker mutation OR pT4 stage strategy. Conclusion: Selection of stage II CC patients for chemotherapy can be improved by either including biomarker status in the selection strategy or by improving adherence to the Dutch guideline recommendations

Model-based evaluation of the cost effectiveness of 3 versus 6 months’ adjuvant chemotherapy in high-risk stage II colon cancer patients

Background: Our aim was to evaluate the cost effectiveness of 3 months’ adjuvant chemotherapy versus 6 months in high-risk (T4 stage + microsatellite stable) stage II colon cancer (CC) patients. Methods: Using the validated PATTERN Markov cohort model, which simulates the disease progression of stage II CC patients from diagnosis to death, we first evaluated a reference strategy in which high-risk patients were treated with chemotherapy for 6 months. In the second strategy, treatment duration was shortened to 3 months. Both strategies were evaluated for CAPOX (capecitabine plus oxaliplatin) and FOLFOX (fluorouracil, leucovorin and oxaliplatin). Based on trial data, we assumed that shortened treatment duration compared with a 6-month regimen was equally effective for CAPOX and less effective for FOLFOX. Adverse events were highest in the 6-month strategy. Analyses were conducted from a societal perspective using a lifelong time horizon. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Incremental net monetary benefit (iNMB) was calculated using a willingness-to-pay value of €50,000/QALY. Results: For CAPOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €41,257 pp. The 3-month strategy resulted in an equal number of CC deaths, but higher QALYs (6.80 pp) and lower costs (€37,645 pp), leading to a iNMB of €8454 per person for 3 months versus 6 months. For FOLFOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €47,135 pp. The 3-month strategy resulted in more CC deaths (393), lower QALYs (6.19 pp) and lower costs (€44,389 pp). An iNMB of −€23,189 was found for 3 months versus 6 months. Conclusion: Our findings indicate that 3 months’ adjuvant chemotherapy should be considered as standard of care in high-risk stage II CC patients for CAPOX, but not for FOLFOX

Longitudinal effects of adjuvant chemotherapy and related neuropathy on health utility in stage II and III colon cancer patients: A prospective cohort study

Patient's quality of life should be included in clinical decision making regarding the administration of adjuvant chemotherapy (ACT) in stage II/III colon cancer. Therefore, quality of life, summarized as health utility (HU), was evaluated for patients treated with and without ACT. Furthermore, the role of chemotherapy–induced peripheral neuropathy (CIPN) on HU was evaluated. Patients diagnosed with stage II/III colon cancer between 2011 and 2019 and participating in the Prospective Dutch ColoRectal Cancer cohort were included (n = 914). HU scores were assessed with the EQ-5D-5L at baseline, 3, 6, 12, 18, and 24 months. Patients treated with ACT received mainly capecitabine and oxaliplatin (57%) or capecitabine monotherapy (40%) (average duration: 3.5 months). HU 3 to 18 months after diagnosis (potential ACT period + 12 months follow-up) was compared between patients treated with and without ACT using a mixed model adjusted for age, sex and education level. Subsequently, the CIPN sensory, motor and autonomy scales, measured using the EORTC QLQ-CIPN20, were independently included in the model to evaluate the impact of neuropathy. Using a mixed model, a significant difference of −0.039 (95% confidence interval: −0.062; −0.015) in HU was found between patients treated with and without ACT. Including the CIPN sensory, motor and autonomy scales decreased the difference with 0.019, 0.015 and 0.02, respectively. HU 3 to 18 months after diagnosis is significantly lower in patients treated with ACT vs without ACT. This difference is on the boundary of clinical relevance and appears to be partly related to the sensory and motor neuropathy-related side effects of ACT

Estimating adjuvant treatment effects in Stage II colon cancer: Comparing the synthesis of randomized clinical trial data to real-world data

There is an ongoing discussion regarding the impact of adjuvant chemotherapy in Stage II colon cancer. We therefore estimated adjuvant treatment effect in Stage II colon cancer using pooled disease-free survival (DFS) data from randomized clinical trials (RCT approach) and compared this to real-world data (RWD approach) estimates. First, we estimated the treatment effect in RCTs by (i) searching relevant trials reporting DFS data, (ii) generating patient-level data from reported DFS data and (iii) estimating treatment effect in the patient-level data. Second, the treatment effect was estimated in an observational cohort of 1,947 patients provided by the Netherlands Cancer Registry using three propensity score methods; matching, weighting and stratification. In the RCT approach, patient-level data of 4,489 patients (events: 853) were generated from seven trials which compared two of the following treatment arms: control, 5FU/LV or FOLFOX. A Cox model was used to estimate a hazard ratio (HR) of 0.77 (0.43;1.10) for 5FU/LV vs. control and 0.93 (0.72;1.15) for FOLFOX vs. 5FU/LV. In the RWD approach, HRs for any adjuvant treatment vs. control were 0.95 (0.50;1.80), 0.88 (0.24;3.21) and 1.05 (0.04;2.06) using matching, weighting and stratification, respectively. There was no significant difference with the estimates from the RCT approach (interaction test, p > 0.10). The RCT data suggest a clinically relevant benefit of adjuvant chemotherapy in terms of DFS, but the estimate did not reach statistical significance. Stratified analyses are required to evaluate whether treatment effect differs in specific subgroups

Live and Incremental Whole-System Migration of Virtual Machines Using Block-Bitmap

In this paper, we describe a whole-system live migration scheme, which transfers the whole system run-time state, including CPU state, memory data, and local disk storage, of the virtual machine (VM). To minimize the downtime caused by migrating large disk storage data and keep data integrity and consistency, we propose a three-phase migration (TPM) algorithm. To facilitate the migration back to initial source machine, we use an incremental migration (IM) algorithm to reduce the amount of the data to be migrated. Block-bitmap is used to track all the write accesses to the local disk storage during the migration. Synchronization of the local disk storage in the migration is performed according to the block-bitmap. Experiments show that our algorithms work well even when I/O-intensive workloads are running in the migrated VM. The downtime of the migration is around 100 milliseconds, close to shared-storage migration. Total migration time is greatly reduced using IM. The block-bitmap based synchronization mechanism is simple and effective. Performance overhead of recording all the writes on migrated VM is very low.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000263868800011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Computer Science, Hardware & ArchitectureEngineering, Electrical & ElectronicEICPCI-S(ISTP)2

Longitudinal effects of adjuvant chemotherapy and related neuropathy on health utility in stage II and III colon cancer patients: A prospective cohort study

Patient's quality of life should be included in clinical decision making regarding the administration of adjuvant chemotherapy (ACT) in stage II/III colon cancer. Therefore, quality of life, summarized as health utility (HU), was evaluated for patients treated with and without ACT. Furthermore, the role of chemotherapy–induced peripheral neuropathy (CIPN) on HU was evaluated. Patients diagnosed with stage II/III colon cancer between 2011 and 2019 and participating in the Prospective Dutch ColoRectal Cancer cohort were included (n = 914). HU scores were assessed with the EQ-5D-5L at baseline, 3, 6, 12, 18, and 24 months. Patients treated with ACT received mainly capecitabine and oxaliplatin (57%) or capecitabine monotherapy (40%) (average duration: 3.5 months). HU 3 to 18 months after diagnosis (potential ACT period + 12 months follow-up) was compared between patients treated with and without ACT using a mixed model adjusted for age, sex and education level. Subsequently, the CIPN sensory, motor and autonomy scales, measured using the EORTC QLQ-CIPN20, were independently included in the model to evaluate the impact of neuropathy. Using a mixed model, a significant difference of −0.039 (95% confidence interval: −0.062; −0.015) in HU was found between patients treated with and without ACT. Including the CIPN sensory, motor and autonomy scales decreased the difference with 0.019, 0.015 and 0.02, respectively. HU 3 to 18 months after diagnosis is significantly lower in patients treated with ACT vs without ACT. This difference is on the boundary of clinical relevance and appears to be partly related to the sensory and motor neuropathy-related side effects of ACT